{"id":"W7084129434","doi":"10.6084/m9.figshare.c.8006015","title":"randPedPCA: rapid approximation of principal components from large pedigrees","year":2025,"lang":"en","type":"other","venue":"Figshare","topic":"Educational Practices and Sociocultural Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pedigree chart; Principal component analysis; Singular value decomposition; Principal (computer security); Inverse; Decomposition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002530865,0.001939549,0.001153269,0.001651129,0.0007156442,0.001766845,0.001897126,0.0009656891,0.01061032],"category_scores_gemma":[0.01559927,0.001054092,0.002170493,0.001596962,0.0006988239,0.0015375,0.002085064,0.002332387,0.006167276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007084359,"about_ca_system_score_gemma":0.002625155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01628656,"about_ca_topic_score_gemma":0.02282893,"domain_scores_codex":[0.9986227,0.0005835386,0.00006522187,0.0002809912,0.0003116985,0.0001358902],"domain_scores_gemma":[0.9960083,0.002443324,0.0001969189,0.0006195648,0.0005873184,0.0001445619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004451072,0.0001643605,0.006106903,0.0006666003,0.0006168115,0.0006061881,0.0006038084,0.3262245,0.009786511,0.03335285,0.07644872,0.5449776],"study_design_scores_gemma":[0.00007911574,0.00003673765,0.001647325,0.00006344107,0.00004126579,0.0002126517,0.00005927423,0.9523753,0.002146639,0.02927331,0.01402129,0.00004358013],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.006931794,0.000393633,0.980507,0.0002549813,0.00008622299,0.00009680952,0.001143652,0.009703483,0.000882526],"genre_scores_gemma":[0.09223991,0.0006369984,0.8940536,0.000293127,0.0001187431,0.0005240676,0.005297367,0.003308416,0.003527845],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01628656,"threshold_uncertainty_score":0.03549504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1120643413216643,"score_gpt":0.40928582827126,"score_spread":0.2972214869495957,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}